Production software, built to be owned
Build-vs-buy, AI agent infrastructure, and technical diligence
Builder, not just an advisor
Companies bring me in to build production software and AI systems. Sometimes the first question is whether to build at all or just license. When the answer is to build, we do it together.
For a medical directorship operating across more than 90 locations in Texas, that meant three connected platforms on a shared backend: 9 portals, ~250 web pages, and around 250,000 lines of code.
And maintaining for them has not meant standing between them and their system. I connected their AI assistants directly to the platform, so a quick question or a request to make a button on the dashboard bigger no longer takes an email thread or a form submission. They ask their assistant, and it opens a request for my review.
- Onboarded clinics
- 52
- Onboarded clinics
- Telehealth visits per week
- 100+
- Telehealth visits per week
- Security incidents or data loss
- 0
- Security incidents or data loss
Also building: Juniper — a multi-agent system that turns plain-language requests into standing automations across any configured service. Instead of re-prompting a model on a schedule, the agent reads the request once and writes a declarative script. That script is validated before it goes live, then run deterministically on schedules and events, calling a right-sized LLM at runtime only for the steps that require intelligence. The architecture is open source.
Build, Buy, Vibe?
Building software has become fast and inexpensive, so the difficult parts are now deciding what to build and maintaining what you have built.
Build
Build the tool deliberately, with a designated owner responsible for maintaining it. That owner may be a member of your team or a contracted engineer.
Buy
License traditional SaaS. You pay a subscription, and the vendor bears the maintenance burden.
Vibe
Vibe-code the tool and deploy it without a designated owner or engineer. No one is responsible for maintaining it.
Offerings
Vibe-Code Health Check
I review the vibe-coded tools your company depends on and report on their risk, maintainability, and operability.
The Build Decision
I cost out maintenance across all three options and help you decide, working from the realities of your organization and evidenced projections of where the tooling is going.
Custom Build
When ownership costs less than licensing, I either advise your team on the build or execute it myself. In either case, you retain direct access to the system, including through your own AI assistants.
How I Engage
Every engagement begins the same way: I learn how your work happens. What follows depends on what I find.
- 01
Embedded Discovery
I embed with your team to learn the workflows, bottlenecks, and undocumented knowledge that process documentation leaves out. The output is a prioritized list of the problems worth solving with software.
- 02
Roadmap & Architecture
I turn that list into a plan: what to build, what to buy, what to shore up, what data and systems work has to come first, and how success is measured.
- 03
Build
The roadmap selects one or more of the following, according to what the situation requires:
Build it for you
Production-grade traditional and agentic software.
Build it with you
I pair with your engineers so that the system's context remains in-house from the outset.
Harden what you have built
I stabilize the vibe-coded tools your company already depends on: tests, documentation, security, and a maintenance plan.
Advise you to buy instead
When a vendor costs less than building and maintaining your own, I recommend the vendor and help you integrate it.
- 04
Ongoing Partnership
A system in production needs a designated owner. That owner may be someone on your team or myself on retainer.
Includes: patching, model migrations, token cost management, monitoring, a defined response window, and new builds on top of what is already running.
Buying a company rather than running one? I run technology and operations diligence for acquirers under LOI→
Looking Ahead
The Three Pillars of Agent Operability
Agent operability is the degree to which your data, systems, and roles are structured for Human ↔ AI collaboration and autonomous agentic work. Each gap in agent operability is a place where your organization does not capture the gains AI can deliver.
Data Organization & Accessibility
I audit how your information is structured, surfaced, and permissioned, then make it discoverable to the humans and agents who need it.
Systems Agents Can Act On
I build the surfaces agents need to act safely: APIs and MCP servers, permissions scoped to each agent, and audit trails for agent actions.
Human ↔ AI Coordination
I map where agents act autonomously, where humans review, and where the two work together, then design the touchpoints and approval flows to match.